Urmo Võsa

This paper identifies novel genetic loci and polygenic risk scores for rheumatoid arthritis using a million-participant meta-analysis and shows improved risk prediction with metabolomic integration.

This study performs a large-scale GWAS on 249 metabolic traits in 619,372 individuals, identifying 88,604 associations and using MR to explore causal links between metabolites and diseases.

The paper performs a federated cis-eQTL meta-analysis across single-cell datasets to identify cell-type-specific genetic effects and link them to disease mechanisms.

This study identifies 1,257 genetic variants associated with human personality traits using large-scale GWAS and finds widespread genetic correlations with behaviors and life outcomes.

The paper uses Estonian Biobank data to identify genetic loci associated with 5,491 disease phenotypes, finding 3,222 genome-wide significant loci and 754 protein-altering variant-trait associations.

This paper links common and rare disease genetics by identifying key genes affected by common variants through gene regulatory networks, finding many key genes are outside GWAS loci.

The paper reviews the Estonian Biobank's role in advancing genomics research and personalized medicine through its comprehensive data and translational focus.

This study identifies shared genetic components between thyroid disorders and reproductive health using GWAS and genetic correlation analysis in 743,088 individuals.

This study identifies metabolites causally linked to type 2 diabetes and its complications, revealing genetic regulation effects and metabolic pathways involved.

This study identifies genetic determinants of plasma protein levels in the Estonian population, including common, rare, and copy number variants, and provides fine-mapped credible sets for 151 proteins.

This study identifies 80 medical conditions associated with ADHD genetic liability in adults without ADHD diagnosis using EHR data.

This paper identifies six genetic loci associated with circulating anti-Müllerian hormone levels in pre-menopausal women through a GWAS meta-analysis, including novel signals and biological pathway insights.

The paper identifies pQTLs for 91 plasma proteins, finds novel associations, and uses MR to uncover causal roles in immune-mediated diseases, suggesting new therapeutic targets.

OTTERS is a TWAS framework that uses summary-level eQTL reference data to estimate eQTL weights and perform omnibus TWAS, showing improved power and applicability.

This study identifies Neandertal DNA's long-range regulatory effects on gene expression in modern humans, showing their influence on immune traits, schizophrenia, and other phenotypes.

This study identifies 114 genome-wide significant rare CNV-disease associations across 30 neurological disorders, revealing 38 novel triplosensitive genes and developing a model to predict dosage sensitivity.

The paper introduces an omics-informed quality score to improve CNV detection and association analysis by reducing false positives and increasing statistical power.

The paper uses blood eQTL meta-analysis to explore the polygenic architecture of complex traits, finding that trans-eQTLs are more informative for identifying causal genes than cis-eQTLs.

This study uses Mendelian randomization to test if SMOX levels causally affect cancer risk, finding no significant association with six cancer types.

This study identifies 592 genetic loci associated with 184 plasma proteins in 26,494 individuals and finds causal relationships between protein levels and disease.

The paper performs a GWAS meta-analysis of cervical cancer and links it to reproductive tract development, immune response, and cellular proliferation/apoptosis, while also identifying genetic risk factors for other cervical phenotypes.

The paper identifies TRAFD1 as a master regulator of IFNγ signalling in celiac disease by systematically prioritizing candidate genes in disease loci using multiple computational methods.

The paper identifies 31 host genetic loci influencing gut microbiome composition through GWAS and suggests causal effects in inflammatory diseases.

The paper uses allele-specific expression analysis in a large cohort to identify high-impact, autosomal-dominant variants that are compensated by imbalanced expression.

The paper introduces Decon2, a method to deconvolute bulk blood eQTL effects into immune cell subpopulations, showing high concordance with experimental and single-cell studies.

The paper identifies pQTLs for cardiovascular proteins and uses them to evaluate drug targets and suggest new candidates for precision medicine.

This paper introduces TWMR, a Mendelian Randomization method that identifies gene-trait associations by integrating GWAS and eQTL data, revealing 3,913 novel associations across 43 human phenotypes.

The paper identifies over 30,000 SNPs affecting regulatory element activity using SuRE reporter technology, linking them to gene regulation and potential human traits.

This study identifies 139 common and 4 rare genetic variants associated with type 2 diabetes through GWAS and integrates gene expression and epigenomic data to highlight potential functional genes and regulatory mechanisms.

The paper identifies gene targets for brain-related traits using transcriptomic and methylomic data from blood, finding strong correlations between genetic effects in brain and blood tissues.